Preprints
https://doi.org/10.5194/wes-2022-114
https://doi.org/10.5194/wes-2022-114
 
09 Jan 2023
09 Jan 2023
Status: this preprint is currently under review for the journal WES.

Comparison Metrics Microscale Simulation Challenge for Wind Resource Assessment

Florian Hammer1, Sarah Barber1, Sebastian Remmler2, Federico Bernardoni3, Kartik Venkatraman4, Gustavo A. Díez Sánchez6, Alain Schubiger1, Trond-Ola Hågbo4,5, Sophia Buckingham4, and Knut Erik Giljarhus5 Florian Hammer et al.
  • 1Eastern Switzerland University of Applied Sciences, Oberseestrasse 10, 8640 Rapperswil, Switzerland
  • 2Wobben Research and Development GmbH, Borsigstr. 26, 26607 Aurich, Germany
  • 3UTD Wind, University of Texas at Dallas, 75080 Richardson, Texas, USA
  • 4von Karman Institute for Fluid Dynamics, 1640 Sint-Genesius-Rode, Belgium
  • 5University of Stavanger, 4021 Stavanger, Norway
  • 6Independent researcher

Abstract. The main goals of a wind resource assessment (WRA) at a given site are to estimate the wind speed and annual energy production (AEP) of the planned wind turbines. Several steps are involved in going from initial wind speed estimations of specific locations to a comprehensive full-scale AEP assessment. These steps differ significantly between the chosen tool and the individuals performing the examination. The goal of this work is to compare different WRA simulation tools at the Perdigão site in Portugal, for which a large amount of wind measurement data is available, in terms of both accuracy and costs. Results from nine different simulations from five different modellers were obtained via the "IEA Wind Task 31 Comparison metrics simulation challenge for wind resource assessment in complex terrain", consisting of a range of linear models, Reynolds-Averaged Navier-Stokes (RANS) computational fluid dynamics models and Large Eddy Simulations (LES). The wind speed and AEP prediction errors for three different met mast positions across the site were investigated and further translated into relative “skill” and “cost” scores, using a method previously developed by the authors. This allowed the most optimal simulation tool in terms of accuracy and cost to be chosen for this site. It was found that the RANS simulations achieved very high prediction accuracy at relatively low costs for both wind speed and AEP estimations. The LES simulations achieved great wind speed prediction for certain conditions, but at a much higher cost, which in turn also reduced the number of possible simulations, leading to a decrease in AEP prediction accuracy. For some of the simulations, the forest canopy was explicitly modelled, which was proven to be beneficial for wind speed predictions at lower heights above the ground, but lead to under-estimations of wind speeds at upper heights, decreasing the AEP prediction accuracy. Lastly, low correlation qualities between wind speed and AEP prediction error were found for each position, showing that accurate wind modelling is not necessarily the only important variable in the WRA process, and that all the steps must be considered.

Florian Hammer et al.

Status: open (until 06 Feb 2023)

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Florian Hammer et al.

Florian Hammer et al.

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Short summary
We further enhanced a knowledge base for choosing the most optimal wind resource assessment tool. For this, we compared different simulation tools for the Perdigão site in Portugal, in terms of accuracy and costs. In total five different simulation tools were compared. We found that with a high degree of automatisation and a high experience level of the modeller a cost effective and accurate prediction based on RANS could be achieved. LES simulations are still mainly reserved for academia.